most citedTransformLLM: Adapting Large Language Models via LLM-Transformed Reading Comprehension Text

1 citations · 1 across the 1 of their papers we have counts for

collaborators

2 papers

cs.LG2025

LORENZA: Enhancing Generalization in Low-Rank Gradient LLM Training via Efficient Zeroth-Order Adaptive SAM

Yehonathan Refael, Iftach Arbel, Ofir Lindenbaum +1

We study robust parameter-efficient fine-tuning (PEFT) techniques designed to improve accuracy and generalization while operating within strict computational and memory hardware co…

cs.CL2024★ 1 cited

TransformLLM: Adapting Large Language Models via LLM-Transformed Reading Comprehension Text

Iftach Arbel, Yehonathan Refael, Ofir Lindenbaum

Large Language Models (LLMs) have shown promise in highly-specialized domains, however challenges are still present in aspects of accuracy and costs. These limitations restrict the…